• Korean Management Science Review
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• v.32 no.4
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• pp.193-207
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• 2015

Government-funded research institutes (GRIs) have played a pivotal role in national R&D in Korea. To achieve desired goals of GRIs with the limited R&D budget, their performance along with time needs to be measured and compared so that appropriate R&D policies can be formulated and implemented. This study measures the dynamic performance of GRIs from the efficiency perspective using the window model of data envelopment analysis (DEA). DEA is a non-parametric approach to measuring the relative efficiency of decision-making units (DMUs) with multiple inputs and outputs, and the DEA window model can capture the dynamic changes in efficiency of DMUs during multiple periods. The relative efficiency of GRIs is measured from the two perspectives: R&D and R&BD. Patents, papers, technology transfers are selected as outputs for R&D while compensated technology transfers and technology royalty are employed as outputs for R&BD. This study measures and compares the two types of performance of 20 Korean GRIs under the control of National Research Council of Science and Technology during the period of six years from 2008 to 2013. The results are expected to provide fruitful implications for national R&D policy making.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.1
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• pp.91-116
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• 2015

This study aims to provide public sectors with eco-efficiency information. To implement the purposes of the study, environmental and economic variables of Eco-Efficiency were identified through decision tree model, then the relative Eco-Efficiencies of 243 public sectors were evaluated through input-oriented DEA (Data Envelopment Analysis) model. Specifically, the amount of public purchasing per a staff and the amount of energy use per a staff were considered as input factors. Sales per a staff was considered as output factor. The result shows that most of the public sectors (94.2%) were evaluated as "inefficient" taking into consideration of average value, 0.501 from market-based public corporations, 0.288 from local public corporations, 0.28 from quasi-market-based public corporations, 0.269 from fund-management-based quasi-governmental institutions, 0.09 from non-classified public institutions, and 0.078 from commissioned-service-based quasi-governmental institutions. Furthermore, it is possible to establish a plan for internal Eco-Efficiency improvement based on information of the reference set. In order to improve the Eco-Efficiency in the public sectors in the long term, environmental impacts of the overall public sectors' operations (e.g., energy saving, water saving, waste reduction, and purchasing of green products) needs to be properly proposed in consideration of BSC (Balanced Scorecard) indicators of public sectors.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.1
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• pp.75-89
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• 2015

In recent years, attention to the high debt ratio in public institutions has pushed the government to make efforts in reducing the debt ratio. However, in order to stimulate the economy, the government needs drastically innovative measures that reduce debt by improving efficiency rather than moderate approaches that focus solely on debt reduction. Despite this need, no study has yet systematically analyzed the overall efficiency of domestic public institutions and identified the source of inefficiencies in each public entity. Therefore, largely two research questions are examined. First, this study compares the efficiency levels by types of public institutions. Second, this study identifies the cause of inefficiencies in each public institution and proposes directions for improving efficiency. Based on a 5-year data of 302 public institutions published in public business information systems and organizational websites from 2009 to 2013, Data Envelopment Analysis (DEA) was performed. The input variables include the number of employees and total costs while the output variables include sales and net income. Reflecting the characteristics of public institutions, the input-oriented CCR model and input-oriented BCC model were utilized. Analysis results are as follows. First, market-oriented public institutions showed the highest efficiency while fund management quasi-governmental agencies showed the highest inefficiency. Second, scale efficiency score was measured by applying the CCR model and the BCC model on the organizations with the lowest efficiency level, fund management quasi-governmental agencies. Based on these analysis results, the source of inefficiency and detailed directions for improvement were proposed for Decision Making Units (DMUs) with low CCR and BCC scores.

• Journal of Distribution Science
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• v.16 no.5
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• pp.91-101
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• 2018

Purpose - This study compares the management efficiency of retailers in China, Korea and other global countries. China's retail industry is experiencing a recession. In order to strengthen the competitiveness of retailers, it is necessary to manage the efficiency. Therefore, we analyzed the management efficiency of Chinese retailers as well as Korea and global retailers who are competing with Chinese retailers. Research design, data, and methodology - The DEA(Data Envelopment Analysis) carried out for evaluating the relative efficiency of multiple DMUs (decision making units) with homogeneity. Data were collected from the American Retail Trade Association (2017). In those distributors' data, 5 of China and 5 of Korea and 10 of other global countries' analyzed. CCR and BCC analysis were performed to determine the cause of the inefficiency of DMUs by measuring the technical efficiency, pure technology efficiency and scale efficiency. Result - Among the 20 retail distributors, Costco, Kroger (Global), Eland World, BGF(Korea) are operating efficiently. Chinese retailers are operating inefficiently. Retailers' CRS status means the growth rate of input is equal to the growth rate of output. In the case of DRS status, the ratio of output to input variable is much smaller. In order to improve inefficiency, reducing input variables can be a solution. For the firms in IRS status, the rate of increase in output is relative greater than the input. That means efficiency is good condition. The analysis result shows that most retailers are showing DRS status especially Chinese retailers. Scale efficiency is a major cause of inefficiency rather than pure technology efficiency. It is recommended for ineffective retailers to reduce inputs to become efficient retailers. Otherwise, retrain existing employees or introducing advanced technologies to increase the output. Conclusions - Most of Chinese retailers are operating inefficiently which caused by the excessive investment in the inputs. On the other hand, Other global retailers are analyzed to be efficient by DEA. In this study, benchmarking targets of some retailers' suggested to improve the management efficiency especially in inputs.

• Advances in Energy Research
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• v.5 no.2
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• pp.179-205
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• 2017

This research presents an in-depth analysis of location planning of the solar-hydrogen power plants for electricity production in different cities situated in Kerman province of Iran. Ten cities were analyzed in order to select the most suitable location for the construction of a solar-hydrogen power plant utilizing photovoltaic panels. Data envelopment analysis (DEA) methodology was applied to prioritize cities for installing the solar-hydrogen power plant so that one candidate location was selected for each city. Different criteria including population, distance to main road, flood risk, wind speed, sunshine hours, air temperature, humidity, horizontal solar irradiation, dust, and land costare used for the analysis. From the analysis, it is found that among the candidates' cities, the site of Lalezar is ranked as the first priority for the solar-hydrogen system development. A measure of validity is obtained when results of the DEA method are compared with the results of the technique for ordering preference by similarity to ideal solution (TOPSIS). Applying TOPSIS model, it was found that city of Lalezar ranked first, and Rafsanjan gained last priority for installing the solar-hydrogen power plants. Cities of Baft, Sirjan, Kerman, Shahrbabak, Kahnouj, Shahdad, Bam, and Jiroft ranked second to ninth, respectively. The validity of the DEA model is compared with the results of TOPSIS and it is demonstrated that the two methods produced similar results. The solar-hydrogen power plant is considered for installation in the city of Lalezar. It is demonstrated that installation of the proposed solar-hydrogen system in Lalezar can lead to yearly yield of 129 ton-H2 which covers 4.3% of total annual energy demands of the city.

• Journal of Navigation and Port Research
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• v.36 no.6
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• pp.527-534
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• 2012

In order to achieve sustainable growth and gain competitive advantages business performance should be monitored regularly by a company. In the port industry container terminal operators are facing growing competition. A large scale of new container terminals are constructed and the number of new container terminal operators are increasing. Container shipping lines are gaining bargaining power against terminal operators in terms of negotiating terminal usage. The competitive environments result in reduced cargo handling charges and poor financial performance of container terminal operators. It becomes very important to examine how efficiently container terminal operators are operating their terminals and how to improve their performance. This paper investigates the measurement efficiency for container terminal operators in Korea using Data envelopment analysis(DEA) of DEA-CCR and DEA-BCC Model. This paper finds out which container terminal operators are inefficient and how to improve their management efficiency.

• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.1030-1036
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• 2009

In 1990's, in Europe and some advanced nations, the structural reform of the railroad industry for improving the productive efficiency of the railroad industry and competitive power had been progressed. This paper empirically explores the relationship between railway restructuring and productive efficiency in the railway industry. We use Data Envelopment Analysis (DEA) to construct efficiency scores, and explain these scores, using Tobit regression analysis by using variables reflecting institutional factors and organizational type. Our results suggest that vertical separation, infrastructure and services are separated, and horizontal separation, passenger service and freight service are separated, improve productive efficiency. We also find that market competition has positive effect on the efficiency, but independent management from the government has negative effect, which is in line with economic intuition as well as with expectations on the railway restructuring. As a consequence, increased independence without sufficient competition and adequate regulation may deteriorate incentives for productive efficiency.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.15-24
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• 2011

This study discusses an equity analysis performed to supplement the existing bus service evaluation system. The equity of 179 feeder bus routes in the city of Seoul(Year 2009) is analyzed by employing the modified BCC model along with the desirable inputs such as a number of bus stops and a frequency of operations. In the analysis, each DMU (Decision Making Unit) is assumed to use the desirable inputs, and produces both the index of equity and the index of accessibility. We apply an input-oriented modified BCC model to analyze the equity of the DMUs. The computational result indicates that only 9% of the feeder bus routes are equitable among the total DMUs and the average equity estimate is 0.702. It is also suggested that on average approximately 60% increases of desirable inputs (i.e., a number of bus stops and a frequency of operations) are needed in order to improve equity of DMU in the city of Seoul. The result of the tobit regression analysis on the determinant factors affecting the equity of DMUs shows that all the independent variables (i.e., a number of bus stops and a frequency of operations) are statistically significant at 5% significance level, and the number of bus stops is found to be the most influential factor.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.505-513
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• 2013

Basketball is one of the most popular winter sports in Korea. Korean basketball league has started in 1997 with 8 teams. Currently, there are 10 teams participating in it and the average number of spectators in 2010~2011 season reached 3,815. However, it has not been making good profit. It would be meaningful to analyze and evaluate the operational efficiency in order to provide basic information to improve the efficiency. This study used data envelopment analysis to figure out comparative efficiency of the teams in the Korean basketball league. As a result, Jeonjaland, LG, and KT were evaluated to be efficient teams and Orions, Ginseng, and Mobis were not.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.358-366
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• 2011

Multi-criteria ABC inventory classification, which aims to classify inventory items by considering more than one criterion, is one of the most widely employed techniques for inventory control. The weighted linear optimization (WLO) model proposed by Ramanathan (2006) solves the problem of multi-criteria ABC inventory classification by generating a set of criterion weights for each inventory item and assigning a normalized score to the item for ABC analysis. However, the WLO model has some limitations. First, many inventory items can share the same optimal score, which can hinder a precise classification of inventory items. Second, the model allows too much flexibility in weighting multiple criteria; each item is allowed to choose its own weights so that it can maximize its score. As a result, if an item dominates the others in terms of a certain criterion, it may be classified into a higher class regardless of other criteria by assigning an overwhelming weight to the criterion. Consequently, an item with a high value in an unimportant criterion and low values in others may be inappropriately classified as class A, leading to an inaccurate classification of inventory items. To overcome these shortcomings, we extend the WLO model by using the cross-efficiency method in data envelopment analysis. We claim that the proposed model can provide a more reasonable and accurate classification of inventory items by mitigating the adverse effect of flexibility in the choice of weights and yielding a unique ordering of inventory items.